Find and replace values by NA for all columns in DataFrame

Question

Age <- c(90,56,51,'NULL',67,'NULL',51)
Sex <- c('Male','Female','NULL','male','NULL','Female','Male')
Tenure <- c(2,'NULL',3,4,3,3,4)
df <- data.frame(Age, Sex, Tenure)

In the above example, there are 'NULL' values as character/string formate. I am trying to impute NA in place of 'NULL' values. I was able to it for a single column as df$age[which(df$Age=='NULL)]<-NA' However I don't want to write this for all columns.

How to apply similar logic to all columns so that all the 'NULL' values of df are converted to NAs? I am guessing that apply or custom defined function or for loop will do it.

Answer 1

base R solution

replace(df, df =="NULL", NA)